Key findings

AI adoption among very small employers doubled—but adoption remains uneven

• AI adoption among very small employer firms doubled in one year, rising from 9.5 percent to 20 percent.
• Solo operators adopt AI at less than half the rate of employer firms—8.4 percent compared with 20 percent—yet 92 percent of solo operators using AI report a positive business impact
• That gap matters because solo operators account for 83.7% of U.S. businesses. The group adopting AI at the lowest rate is also by far the largest segment of Main Street.

For solo operators, the principal barrier is perceived relevance—not skill

• Solo operators are not more likely than employer firms to report difficulty keeping up with technology, a lack of technical skills, or little interest in AI. They are, however, considerably more likely to believe that AI does not apply to their work.
• Nearly one-third of solo operators—32%—say AI is not relevant to their business, compared with 21% of firms with employees.
• Yet among solo operators who do adopt AI, 92% report a positive business impact. For owners working without employees, AI may function less like an optional technology and more like a first source of additional capacity.

Digital readiness is the clearest pathway to AI adoption

• Whether a business has a website or social media presence is the strongest observable predictor of AI adoption.
• Businesses with an online presence report AI use at nearly seven times the rate of businesses without one: 19.3 percent compared with 2.8 percent.
• The divide extends across the adoption process. Digitally connected non-users are also more than three times as likely to plan to adopt AI within the next year.
• These findings suggest that AI readiness builds on digital readiness.
• Investments in websites, social media, e-commerce, digital payments, and other foundational tools may also help owners recognize where AI fits into their business.

Small businesses are using AI to address operational pressure

• AI adopters are not necessarily the businesses facing the fewest constraints. In fact, AI users report more challenges than non-users in areas including taxes, establishing an online presence, finding customers, and accessing capital.
• At the same time, adopters and non-adopters report nearly identical levels of confidence using digital technologies.
• The findings suggest that AI adoption may be driven less by technological sophistication than by the search for practical ways to extend limited business capacity. Many of the tasks where small businesses use AI—such as preparing documents, creating content, analyzing information, and supporting business planning—correspond to work that owners may not have the staff or resources to hire out.

Latino business owners are leading adoption

• Latino small business owners report using AI at more than twice the rate of white owners: 24.8% compared with 10.3%.
• The difference remains after accounting for education, income, digital presence, industry, and other business characteristics.
• Black owners also show a similar directional pattern, while women and men report comparable adoption rates.
• These findings, together with evidence suggesting that AI adopters are more likely to report support challenges, suggest that AI is helping business owners navigate growth and address unmet support needs.

What this means for the small business ecosystem

The challenge is not simply to raise awareness of AI. It is to help owners see where AI fits into the work they already do—and then support them in turning experimentation into repeatable business practices. The brief identifies six priorities for business support organizations, community development financial institutions, lenders, policymakers, funders, and other ecosystem partners:

1. Focus AI education on concrete operational needs rather than general awareness.
2. Treat foundational digital infrastructure as a prerequisite for broader AI adoption.
3. Pair demonstrations with hands-on assistance that helps owners integrate AI into workflows.
4. Prioritize solo operators and businesses without an online presence.
5. Use examples and demonstrations led by peers in similar businesses.
6. Track adoption, use cases, and business outcomes over time.

Whether AI widens or narrows gaps among small businesses may depend less on the technology itself than on whether owners receive the support needed to put it to practical use.

About the research

The brief is based on AEO’s analysis of the 2025 Entrepreneurship in the Population Survey, conducted by NORC at the University of Chicago.

EPOP:2025 is a nationally representative, probability-based survey of entrepreneurship and business ownership in the United States. AEO developed and funded survey questions examining generative AI use, business applications, perceived impacts, adoption plans, and confidence using digital technologies.

The analysis focuses on business owners with fewer than 10 employees, including both solo operators and firms with one to nine employees. Survey weights were applied to produce nationally representative
estimates.

About the author

Lori Smith, PhD, Head of Research & Insights at the Association for Enterprise Opportunity, authored the brief.

Suggested citation

Smith, Lori. The Main Street AI Paradox: The Smallest Businesses May Have the Most to Gain from AI—and Face the Greatest Constraints to Making It Work. Association for Enterprise Opportunity, June 2026.